In this paper, we study an evolutionary algorithm employed to design and optimize a local control of chaos. In particular, we use a multi–objective fitness function, which consists of the objective function to be optimized and an auxiliary quantity applied as an additional driving force for the algorithm. Numerical results are presented illustrating the proposed scheme and showing the influence of employing such a multi–objective fitness function on convergence of the algorithm.
CITATION STYLE
Richter, H. (2002). An evolutionary algorithm for controlling chaos: The use of multi–objective fitness functions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2439, pp. 308–317). Springer Verlag. https://doi.org/10.1007/3-540-45712-7_30
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